Triple
T30474857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norma Zimmer |
E775413
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Randal Zimmer
Randal Zimmer was the husband of American singer and longtime Lawrence Welk Show "Champagne Lady" Norma Zimmer.
|
E1916921
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Randal Zimmer | Statement: [Norma Zimmer, spouse, Randal Zimmer]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Randal Zimmer Triple: [Norma Zimmer, spouse, Randal Zimmer]
Generated description
Randal Zimmer was the husband of American singer and longtime Lawrence Welk Show "Champagne Lady" Norma Zimmer.
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f22497341481909c21ba329fadaa6b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68718543c8190a173db3534b3c8ea |
completed | May 2, 2026, 11:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a27ac20b53c8190b682b91027969aeb |
completed | June 9, 2026, 6:01 a.m. |
| NEDg | Description generation | batch_6a27adabe9f0819084d8e5c2fb9814be |
completed | June 9, 2026, 6:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a27ae325ec08190b25d909583210fc3 |
completed | June 9, 2026, 6:09 a.m. |
Created at: April 29, 2026, 8:11 p.m.